The field of medical imaging has seen significant advances since the time X-Rays were first used to determine anatomical abnormalities. Medical imaging hardware has progressed in the form of newer machines such as Magnetic Resonance Imaging (MRI) scanners, Computed Axial Tomography (CAT) scanners, etc. Because of the large amount of image data generated by such modern medical scanners, there has been and remains a need for developing image processing techniques that can automate some or all of the processes to determine the presence of anatomical abnormalities in scanned medical images.
Recognizing anatomical structures within digitized medical images presents multiple challenges. For example, a first concern relates to the accuracy of recognition of anatomical structures within an image. A second area of concern is the speed of recognition. Because medical images are an aid for a doctor to diagnose a disease or condition, the speed with which an image can be processed and structures within that image recognized can be of the utmost importance to the doctor reaching an early diagnosis. Hence, there is a need for improving recognition techniques that provide accurate and fast recognition of anatomical structures and possible abnormalities in medical images.
One example of an anatomical structure that is often studied in medical images is the spine. Digital images of the spine may be reconstructed by using raw image data obtained from an MRI scanner. Such digital images are typically either a two-dimensional (“2-D”) image made of pixel elements or a three-dimensional (“3-D”) image made of volume elements (“voxels”). Three-dimensional images may be reconstructed by stacking individual slices one on top of the other. Multiplanar reconstruction (MPR) is a method of reconstruction that builds the image volume by stacking axial slices and cuts slices through the volume in a different MPR plane for visualization. By reformatting the volume, it becomes much easier to visualize the position of one vertebral body in relation to the others.
Vertebral bodies may be automatically labeled to facilitate more efficient interpretation of medical images. Although vertebrae labeling can provide useful information to radiologists, improper visualization or placement of vertebral labels may adversely affect image interpretation.